A single-channel SAR-GMTI algorithm based on sub-apertures and FrFT

Multidimensional waveform encoding is a new multiple-input multiple-output (MIMO) technique for remote sensing. The orthogonality is acquired by digital beamforming in elevation. It has a potential to enhance ground moving target indication (GMTI) performance due to the larger along-track virtual array of the radar system. This paper proposed two modes for GMTI based on multidimensional waveform encoding: intrapulse azimuth beam scanning and intrapulse azimuth encoding. Compared to the phased-array GMTI systems, the mode with intrapulse azimuth beam scanning has improved area search rates, and the mode with intrapulse azimuth encoding has improved minimal detectable velocity performance. Theoretical analysis and simulation results demonstrate that the proposed modes have better performance than the phased-array GMTI systems.

The 2-D Fractional Fourier Transform (FRFT) has been shown to be applicable to the Synthetic Aperture Radar (SAR) imaging problem. Streamlined versions presented here makes the 2-D FRFT comparable with and slightly faster than the Range Doppler (RD) and Extended Chirp Scaling (ECS) methods. The 2-D FRFT is streamlined by eliminating redundancy due to the fact that the same fractional angle is applied to each pulse in the SAR phase history's range dimension while one other fractional angle is applied across each range-gate in the phase history's azimuth dimension. Eliminating the redundancy and approximating the 2-D Fractional Fourier Transform operation in each dimension produces several streamlined 2-D FRFT methods as well as a very fast approximate 2-D FRFT. The computational order of the fast approximate 2-D FRFT is less than that of other corrective SAR imaging techniques. Examples of SAR imaging with these streamlined and approximate FRFTs are given as well as a comparison of the computational speed and impulse response of the full, streamlined and approximate 2-D FRFT, and the RD and ECS methods of SAR imaging.

In this paper, we present the results of a modeling study to examine the interference effect of microDopplers caused by offshore wind farms on airborne sensors operating in the synthetic aperture radar (SAR) and ground moving target indicator (GMTI) modes. The modeling is carried out by generating CAD instantiations of the dynamic wind turbine and using the high-frequency electromagnetic code Xpatch to perform the scattering calculations. Artifacts in the resulting SAR and GMTI signatures are evaluated for interference with tracking of boats in coastal waters. Results of signal filtering algorithms to reduce the dynamic turbine clutter in both SAR images and GMTI displays are presented.

FrFT-CSWSF: Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

The 3-D Fractional Fourier Transformation (FrFT) has unique applicability to multi-pass and multiple receiver Synthetic Aperture Radar (SAR) scenarios which can collect radar returns to create volumetric reflectivity data. The 3-D FrFT can independently compress and image radar data in each dimension for a broad set of parameters. The 3-D FrFT can be applied at closer ranges and over more aperture sampling conditions than other imaging algorithms. The FrFT provides optimal processing matched to the quadratic signal content in SAR (i.e. the pulse chirp and the spherical wave-front across the aperture). The different parameters for 3-D linear, circular, and orbital SAR case are derived and specifi…c considerations such as squint and scene extent for each scenario are addressed. Example imaged volumes are presented for linear, circular and orbital cases. The imaged volume is sampled in the radar coordinate system and can be transformed to a target based coordinate system. Advantages of the FrFT which extend to the 3-D FrFT include its applicability to a wide variety of imaging condition (standoff range and aperture sub-sampling) as well as inherent phase preservation in the images formed. The FrFT closely matches the imaging process and thus is able to focus SAR images over a large variation in standoff ranges specifi…cally at close range. The FrFT is based on the relationship between time and frequency and thus can create an image from an under-sampled wave-front. This ability allows the length of the synthetic aperture to be increased for a fixed number of aperture samples.

Ground moving target indication (GMTI) plays an important role in surveillance and reconnaissance applications, but it is a difficult problem due to the impacts of stationary clutter. This paper proposes a multichannel synthetic aperture radar (SAR) using waveform diversity, namely, multiple-input multiple-output (MIMO) SAR and distinct carrier frequency for GMTI applications. The proposed approach employs MIMO configuration with multiple antennas in azimuth and orthogonal waveform diversity. In doing so, multiple independent transmit-receive channels are formulated at the receiver. Since each antenna uses both waveform diversity and distinct carrier frequency, after clutter cancellation and noise suppression by the displaced phase center antenna (DPCA) and along-track interferometry (ATI) combined processing algorithm, the cross-track velocity is estimated through double-interferometry processing. Next, the Doppler parameters of moving targets are estimated with the fractional Fourier transform algorithm and then GMTI is obtained by a joint signal processing algorithm. Finally, the moving targets are focused with a general chirp scaling imaging algorithm. All the proposed methods are verified by simulation results.

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

This paper investigates different metrics for ground moving target indication (GMTI) with a multichannel synthetic aperture radar (SAR). These metrics are especially sensitive to targets that have an across-track component of velocity, v/sub y/, although they can also detect targets with an along track velocity component, v/sub x/. Not only are the metrics suitable for fully SAR compressed data, they are also meaningful when computed for range (pulse) compressed but Doppler uncompressed data (raw data). The use of both data domains allows for target detection over a larger v/sub y/ range than either used individually. For large v/sub y/, side-lobe suppression in fully SAR compressed data simultaneously suppresses the targets, giving an advantage to the raw data domain. For low v/sub y/, and especially with low RCS targets, the SAR compression gain facilitates detection, giving an advantage to the SAR compressed domain. By viewing the SAR compression as the application of a linear filter, the metrics are shown to be suitable for target detection after any linear filtering of the raw data, such as a linear time-frequency filter, or a simple transformation into the Doppler domain using an FFT filter. The metrics have in common that they are all based on the eigenvector decomposition of the sample covariance matrix. Their statistical properties are analytically compared and their detection capabilities are demonstrated on measured two-channel airborne SAR data in a variety of data domains. Some metrics are shown to allow target detection with low false alarm rates even in heterogeneous terrain, such as in urban areas, without compromising the probability of detection.

In high-resolution (HR) and very-high resolution (VHR) synthetic aperture radar (SAR) images, focus is now on the patch-oriented image categorization in contrast to the pixel-based classification in low-resolution SAR images. SAR image categorization requires the generation of a compact feature descriptor that accurately defines the content of the image patch under consideration. In this paper we propose a parametric feature descriptor generated on the complex-valued SAR image within a transformation space. The fractional Fourier transform (FrFT), has been considered to transform the image pixels of the single-look complex (SLC) SAR images in order to obtain a simpler statistical response. The real and imaginary components of the complex-valued FrFT coefficients have been modelled with generalized Gaussian distribution (GGD). The proposed feature descriptor is compared with a Wavelet-decomposition-based parametric feature descriptor; and with the FrFT-based and Gabor-filter-bank-based non-parametric feature descriptors. Categorization accuracy enhancement is demonstrated over several categories comprising of natural topologies. The experimental database consists of 2000 image patches (of size 200 × 200 pixels) extracted from SLC HR TerraSAR-X scenes.

This letter addresses an efficient algorithm for ground moving target detection and estimation of motion parameters by synthetic aperture radar (SAR). The proposed method outperforms the conventional robust principal component analysis (RPCA)–based ground moving target indication (GMTI) methods that were proposed in the literature. The ability to estimate the radial and along-track velocities of ground moving targets is provided. The rank constraint in the conventional RPCA problem will be automatically relaxed by employing a dictionary matrix for clutter representation. Thus, the new optimization problem will be solved easier with lower degrees of freedom. Furthermore, this dictionary helps to suppress the clutter of higher Doppler frequencies in case of wind blowing scenarios and intrinsic clutter motion modeling. By employing another dictionary matrix for all possible moving targets with different location and velocity, each solution of the optimization problem will be reasonable as it corresponds to a moving target. Although, the two dictionary matrices impose extra computational burden, this load will be prepared prior to other GMTI processing by the information of the SAR system and scenario parameters. Moreover, the algorithm is proposed for the single-channel SAR configurations and has lower computational load than the conventional RPCA-GMTI methods that have to process the recorded data of multichannel systems. Numerical and experimental results are used to evaluate the performance of the proposed method and validate the theoretical discussions.

This paper addresses four-dimensional ground moving target indication (GMTI) using a multi-channel wide band (WB) synthetic aperture radar (SAR) system. With no acceleration attached to the target the motion of the target is related to two ground and two speed coordinates. However, four other dimensions are used in WB SAR GMTI processing during the detection phase: azimuth, range, bearing, and the relative speed between the object and the SAR platform. In the detection phase, blind hypotheses are used, and the discretization steps between the hypotheses are a trade-off between the number of hypotheses tested and detectability. As the integration angle increases, the step size in the image dimensions and in the relative speed has to be reduced. In this paper we determine the discretization step in all four dimensions for moving target detection, and relate it to radar system parameters. The discretization is derived from the moving target impulse response, assuming independency between the dimensions. In the paper the number of hypotheses per square meter is given for an airborne low frequency and a microwave GMTI WB SAR system.

Multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has drawn considerable attention for its wider detected swath without decreasing PRF compared to the traditional multichannel synthetic aperture radar (MC-SAR) system. For MIMO SAR system, how to extract the matched signal or suppress the unmatched interferences is the foremost task. Using the OFDM chirp signals as the transmitted signals, the robust principal component analysis (RPCA) based method can be employed for ground moving target indication (GMTI) with no need for separating the matched signal and unmatched interferences. The simulation demonstrates the effectiveness of RPCA based method for GMTI in MIMO SAR system.

Moving targets localization is an important challenge in current synthetic aperture radar (SAR) — ground moving target indication (GMTI) system. The along track interferometry (ATI) method is usually used for GMTI in SAR, however, which suffers from ambiguous parameters estimation due to wrapped phase and less robust to estimation errors (of system parameters and motion parameters of the moving targets). Focusing on these, we propose a new neural network based method to improve the moving targets localization performance. After analyzing the main error source of the conventional ATI method, we utilize an error back propagation (BP) neural network to replace the processing after range compression in the ATI method. And the proposed method is proved effective by the experiments, and it performs much better than the conventional ATI method in localization accuracy, efficiency and robustness.

The fractional Fourier transform (FrFT), which is a generalized form of the well-known Fourier transform, has opened up the possibility of a new range of potentially promising and useful applications including radar involving the use and detection of chirp signals, pattern recognition and Synthetic Aperture Radar (SAR) image processing. The Chirp Scaling Algorithm (CSA) is one of the most important and well-known radar imaging algorithms. It is attractive because of its excellent focusing ability and implementation simplicity. Benefiting from the inherent structure of the FrFT for non- stationary digital signal processing and analysis, especially for chirped-type signals, a new version of the CSA based on the Fractional Fourier Transform (FrFT) is developed. The introduced Fractional Chirp Scaling Algorithm (FrCSA) applied the Fast Fourier Transform (FFT) instead of the fractional Fourier transform (FrFT) in the azimuth direction for the analytical development tractability purposes only as it numerically tractable in both dimensions. To demonstrate the resolution and focusing enhancement in the azimuth dimension using the FrCSA and also to be able to perform azimuth fractional filtering, noise removal and flight path nonlinearity compensation, a closed form expression for the azimuth fractional transformation is required. In this talk we present the mathematical derivation for a closed- form expression of the azimuth-fractional Fourier transform of the new FrCSA with application to high resolution imaging. Results to real SAR data images will show significantly enhanced features using the FrFT-based azimuth expression instead of the classical FFT-based one within the fractional chirp scaling algorithm or any other chirped-type SAR imaging algorithm.

The azimuth multichannel synthetic aperture radar (SAR) system is used in ground moving target indication (GMTI). But for Ka-band SAR, the conflicts between high gain and wide swath coverage are very strict. The digital beamforming (DBF) scan-on-receive (SCORE) algorithm can solve this problem very well. This letter introduces a multichannel SAR system with three receiving antennas in the azimuth direction. For each azimuth antenna, eight subapertures are arranged in the elevation direction in order to obtain higher gain and a lower data rate through the DBF-SCORE algorithm. Airborne flight experiments with this system are accomplished successfully and quantities of experimental data are acquired. In this letter, we first derive the signal forms and weighting coefficients in the DBF-SCORE procedures. Then, different GMTI methods including along-track interferometry and displaced phase center antenna are introduced for azimuth multichannel SAR–GMTI based on the DBF-SCORE technology. Finally, airborne raw data with cooperating moving targets are processed successfully, and the estimation errors of the radial velocities meet the expected accuracy requirements.